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      脾边缘区淋巴瘤发病机制研究进展 Translated title: Advances in molecular genetics pathogenesis of splenic marginal zone lymphoma

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          脾边缘区淋巴瘤(splenic marginal zone lymphoma,SMZL)是一类惰性小B淋巴细胞增殖性疾病,在非霍奇金淋巴瘤(NHL)中的比例约为2%,多见于老年人。以脾脏增大、外周淋巴细胞增多为主要表现,常累及脾脏、骨髓和外周血。1992年Schmid等[1]最早提出SMZL这一分类。SMZL的确诊主要依赖于脾活检,对于无法进行脾活检的患者,如果有典型的血液、骨髓形态学及免疫表型且骨髓活检证实为此CD20+的细胞骨髓窦内侵犯,也可以诊断为SMZL。由于缺乏特异性生物学特征以及反映疾病本质特征的遗传学肿瘤标志物,目前临床上仍有一些病例难以与其他小B细胞淋巴肿瘤鉴别。近年来,随着二代测序技术,特别是全外显子组测序等高通量分析技术的广泛应用,SMZL相对特异的细胞遗传学、分子遗传学及表观遗传学改变得以被发现,从而揭开了SMZL分子生物学发病机制的神秘面纱,为SMZL的诊疗提供了新思路。 一、肝炎病毒感染 边缘区淋巴瘤(MZL)与慢性感染的关系密切。目前发现,丙型肝炎病毒(HCV)与NHL,特别是MZL和弥漫大B细胞淋巴瘤(DLBCL)相关,HCV慢性感染的人群中NHL的患病率是正常群体的35倍[2]。流行病学数据最先证明SMZL与HCV感染的关系,其作用机制目前主要有以下三种假说:①HCV病毒在细胞内复制的产物有致癌作用;②“hit and run”原理:HCV病毒进入细胞并插入序列,诱导细胞原癌基因或抑癌基因发生改变,如Bcl-6、p53、免疫球蛋白重链(IgH)和β连接蛋白基因等[3];③慢性持续的抗原刺激使B细胞增生,HCV核心抗原或E2糖蛋白可激活B细胞表面受体,从而激活B细胞[4]。目前比较得到认可的是最后一个假说。证明HCV在SMZL的发生、发展机制中起重要作用的最有力证据是抗HCV治疗可以逆转肿瘤进程。Hermine等[5]对9例HCV阳性的SMZL患者进行α-IFN单纯抗病毒治疗后,患者外周血常规恢复正常,脾脏大小至少可缩小至原来的50%,长期随访发现,维持HCV RNA阴性的患者SMZL本病也处于长期缓解状态,而部分患者HCV复发的同时也伴随SMZL进展。结果显示抗病毒治疗过程中,SMZL疾病的反应率和缓解程度均与HCV的根除与否明显相关。由此可见HCV感染在SMZL的发生、发展中起重要作用,但具体作用机制有待于进一步研究证实。 我国是HBV感染的高流行地区,2006年统计学数据显示HBV表面抗原阳性率为7.18%,感染率高于HCV感染,HBV感染者比例占全球感染者的三分之一。国内有研究报道NHL患者HBV阳性率可达20%~40%[6]–[7],明显高于国外报道。目前流行病学资料显示SMZL与HBV存在一定的相关性,但HBV在SMZL发生中的作用机制仍未见确切报道,有必要进一步深入研究。 二、IgHV分子特征 (一)IgHV基因突变状态 IgH基因是正常成熟B细胞表达的基因,B淋巴细胞在生发中心发育过程中,互补决定区(CDR)遭遇抗原识别,发生IgH类别转化及体细胞高频突变(SHM),生成特异性抗体。SHM是细胞源自生发中心的标志,检测IgHV的突变状态是追踪肿瘤发展阶段的有效依据。早期研究认为,SMZL细胞均存在着IgHV基因的SHM,提示其可能起源于记忆B细胞[8]。然而实际上10%~30%的SMZL患者有100%的胚系VH基因符合率,即存在IgVH的未突变型[9]。Salido等[10]对SMZL患者进行IgHV突变分析,发现14%的患者有100%的胚系IgHV基因符合率,若根据慢性淋巴细胞白血病(CLL)的划分标准,以与胚系基因98%的符合率为界分为“未突变组”与“突变组”,“未突变组”可占41%。由此说明SMZL中有近一半的患者IgHV处于未突变或低突变状态。后续研究发现,IgHV未突变组患者的细胞遗传学异常更为常见,尤其易出现7q缺失和TP53缺失[11];IgHV未突变型与疾病进展和不良预后明显相关,是SMZL患者的独立不良预后因素[12]。 (二)IgHV家族的偏向性使用 不同的抗原刺激可以影响成熟B细胞的IgHV片段重排,进而影响细胞内VH基因家族的使用率。不同病理类型的淋巴瘤患者其VH家族的使用率也存在差异,VH家族的偏向性使用特征提示疾病发展过程中可能受到特定抗原的刺激,其在淋巴瘤发病中意义也值得深入研究。 对VH基因家族进行偏向性分析,发现SMZL对VH1-2家族有着特殊的嗜好,其中IgHV1-2*04等位基因出现频率最高,这种IgHV1-2*04基因片段的非随机使用可以在20%~30%的SMZL患者中检出[9],[13]–[14],这部分患者的Ig具有较特异的偏长CDR3片段,且该亚组的IgHV基因大多表现为低水平SHM(与胚系基因符合率超过97%)。这种IgHV克隆重排及分子特征的特异性与其他小B细胞淋巴增殖性疾病有明显区别,有可能成为鉴别诊断的分子标志物。同时,也表明SMZL可能源自一组高选择的B细胞群,SMZL的肿瘤细胞发生过程与特定的抗原刺激有关,而IgHV的偏向性使用在HCV阳性组和阴性组均可见[15],这表明抗原刺激在SMZL发生、发展机制中的作用并不仅限于HCV抗原,还存在着其他抗原表位,然而其对应的特定抗原尚未明确[16]。3%~20%的SMZL患者可出现自身免疫性疾病(autoimmune disease,AID)症状,如自身免疫性溶血性贫血(AIHA)、原发免疫性血小板减少症等。Brisou等[17]根据有无AID症状将SMZL患者进行分组,发现在无AID症状者中IgHV1-2*04阳性率为23%,在有AID症状者中阳性率为55%,在有AIHA症状者中阳性率为77%。提示IGHV1-2基因的偏向性使用可能与自身免疫失调有关。同时IgHV1-2家族的偏向性使用也易与7q缺失、14q易位等染色体核型异常同时出现[10]。因此推测SMZL的发生可能是抗原刺激及遗传学改变共同作用的结果。 三、细胞遗传学改变 染色体易位可导致原癌基因的激活促进肿瘤发生,也可使相邻的基因融合并表达相关产物,影响细胞增殖与凋亡,在淋巴瘤的发生、发展机制中起重要作用,如套细胞淋巴瘤(MCL)中常见的t(11,14)/IGH-CCND1,滤泡性淋巴瘤(FL)中的t(14,18)/IGH-BCL2,黏膜相关淋巴组织淋巴瘤(MALT)淋巴瘤中的t(11,18)/BIRC3-MALT1及t(1,14)/LGH-BCL10。然而在SMZL中平衡性染色体异常并不多见,这进一步证明了SMZL是独立于其他B细胞淋巴瘤的一个特殊的分型。 复杂的细胞遗传学异常在SMZL中较为常见。Salido等[10]对330例SMZL患者进行核型分析,72%存在核型异常,其中53%为复杂核型异常。最常见的异常是7q21-36缺失(39%),其次是3q扩增(25%),另外还可见12q扩增、6q缺失、14q易位等,但重现性均不高。大量研究证实SMZL患者中重现性最高的细胞遗传学异常是3q扩增(20%~30%)及7q缺失(30%~50%),其中重现性最高的是7q32缺失[18]–[19]。然而这两种染色体异常并不具有特异性,如3q扩增还见于部分MCL和MALT,7q32缺失在部分急性髓系白血病、肝脾T细胞淋巴瘤、霍奇金淋巴瘤中也有报道,但3q扩增及7q32缺失在SMZL中重现性较高,一定程度上反应了SMZL的分子生物学特性,作为分子标志物在鉴别诊断中可起到一定的提示作用。为进一步探讨疾病的发生机制,有研究者试图通过基因测序及基因表达分析寻找与核型改变高度相关的基因异常,其中一个小样本的比较基因组通过研究发现,位于缺失部分7q36.2的SHH基因和位于7q32.32的POT1基因可能在SMZL的发生中起一定作用[20],但这一分子机制并未得到进一步的认证。大部分研究者认为,7q染色体缺失部位并不存在有效的致病基因[19],取而代之的是编码着大量miRNA[21]。一项大样本的预后分析研究结果显示,7q缺失、3q扩增对SMZL患者的预后无影响[10]。因此除了细胞遗传学异常,可能还存在着与核型改变无关的基因突变或表观遗传学改变,在SMZL的发生、发展中起重要作用。 四、分子遗传学改变 深度基因测序可以发现肿瘤特征性的基因突变或表达异常,并与参与细胞生长分化的重要信号通路相结合,可以进一步解释肿瘤的分子发病机制。过去的研究表明SMZL表现出一个多样的基因突变谱,但研究例数较少(6~15例),大多数基因的突变率均小于10%,重现性较差,说明SMZL遗传学改变的异质性较高或因缺乏大规模研究以探讨其真正的遗传学变化。近年来随着基因测序技术的发展,几项大样本量的分子遗传学研究结果显示在SMZL患者中有意义的基因突变超过30个,其中NOTCH2和KLF2重现性最高,其他基因可重现性较差[9],[12],[13],[22]–[23],但进一步研究发现这些突变基因涉及的通路异常有高度重现性,边缘区B细胞发育相关通路异常[NOTCH通路异常,NF-κB通路激活,B细胞受体(BCR)及Toll样受体(TLR)信号增强等]与60%的SMZL发生机制均有着重要关系,另外DNA修复及细胞周期调控异常也起重要作用[9],[24](表1)。 表1 较大规模(例数>90)脾边缘区淋巴瘤重现性较高基因的分析研究结果(%) 研究者 例数 NOTCH2 KLF2 CARD11 MYD88 TNFIP3 IKBIKB BIRC3 TRAF3 TP3 ARID1A MIL2 Parry等[12] 175 10 12 - 7 7 - - - 15 6 11 Rossi等[9] 117 21 - 7 5 7 7 5 - 15 10 15 Clipson等[22] 96 17 42 11 10 15 11 13 - - Piva等[13] 96 31 20 - - - - - - 13 - - Kiel等[23] 99 25 - - - - - - - - - - Rossi等[25] 101 - - - - 13 3 11 10 - - - 注:-:未检测 (一)NOTCH2突变 NOTCH2突变见于10%~31%的SMZL患者中,全外显子测序分析发现,NOTCH2的突变主要发生在C羧基端的PEST结构域,PEST结构域突变导致NOTCH受体胞内区泛素介导的蛋白酶解失调,从而导致NOTCH通路的持续激活[9]。NOTCH2在边缘区B细胞发育过程中起重要调节作用,脾脏的过渡期B细胞可以分化为滤泡型B细胞和边缘区B细胞,Delta样配体1(DL1)结合并激活NOTCH2受体,使B细胞向边缘区分化[26]。 进一步研究发现,NOTCH2信号主要通过调节下游靶基因的表达来影响边缘区的发育,Fos基因高表达于CD21阳性的边缘区B细胞,NOTCH2敲除会减少Fos的表达而抑制过渡期细胞向边缘区B细胞分化,由此推测NOTCH2通过上调Fos表达来促进边缘区细胞发育[27]。Hes-5和Deltex-1也是NOTCH2的靶基因,高表达于边缘区B细胞,同时也受NF-κB通路的调节,另外多项研究也表明NOTCH2是NF-κB通路的一个重要的上游调控因子,存在复杂的协同作用[28]。Thomas等[29]还发现NOTCH可协同BCR/CD40通路共同促进B细胞的激活,进而促进肿瘤发生。另外,NOTCH通路相关的其他基因,如NOTCH1、SPEN、DTX1突变在SMZL中也具有重现性。Hampel等[30]发现NOTCH2基因突变的小鼠仅出现边缘区细胞的增殖,并不会导致SMZL的发生,这表明SMZL是多种基因多种通路共同作用的结果。因此NOTCH通路在SMZL的发生、发展中起重要作用,还可与NF-κB通路、BCR通路起协同作用。 (二)KLF2突变 Clipson等[22]对96例SMZL进行全外显子组测序,发现Kruppel样转录因子2(KLF2)的突变率达42%,而在其他B细胞淋巴瘤中较罕见。KLF2突变在SMZL的高度重现性在随后的两个研究中被证实[12]–[13],然而在2015年之前对SMZL的多项基因分析研究中均未检测出KLF2突变,可能是因为KLF2序列较长,GC含量高,检测较为困难[31],因此KLF2在SMZL中的作用还需进一步证实。 目前认为KLF2是SMZL的早期的克隆性突变,与7q缺失、IgHV1-2重排、NOTCH2及NF-κB通路突变的出现均密切相关,证明KLF2突变可能参与其他遗传学异常的发生,与其他基因突变协同作用参与肿瘤发生。在正常的淋巴细胞中,KLF2通过与启动子结合等方式调节基因表达,参与调节细胞周期(靶基因p21)及参与细胞迁移过程(EZH2、CCR5)。KLF2在成熟B细胞的分化、活化和转运方面起关键作用。KLF2的缺陷会导致B-1细胞凋亡增加,而边缘区B细胞数目明显增加,同时,KLF2缺陷的滤泡B细胞还表现出正常的边缘区B细胞的表面分子特性[32]。KLF2还会通过TNFα、MYD88、CARD11、BAFF来抑制NK-κB的活性,因而KLF2突变还会激活NK-κB信号通路。然而,单纯KLF2失活仅导致边缘区的扩张,并不能直接导致肿瘤的发生,这表明SMZL的发生机制是复杂多元的,可能其遗传学变异和BCR构型改变的共同作用促使了肿瘤的发生[33]。 (三)NF-κB通路 NF-κB通路是淋巴瘤发生机制中的一个重要通路,在促进B淋巴细胞的增殖、分化中起重要作用。研究表明,有58%的SMZL患者发生NF-κB通路相关基因的突变[33]。NF-κB的经典途径(TNFAIP3、IKBKB)和非经典途径(BIRC3、TRAF3、MAP3K14)相关基因的突变在SMZL中都有重现性。另外MYD88的L265P错义突变见于7%~15%的SMZL患者,CARD11突变率达7%~11%[34],MYD88及CARD11分别调节BCR和TLR信号通路,导致NF-κB信号通路的异常。而SMZL另外两个重现性较高的NOTCH2突变和KLF2突变也均与NF-κB起协同作用,NF-κB通路的异常在边缘区B细胞发育中有关键作用,可能在SMZL的发生、发展中发挥基础性作用。 (四)染色体重塑与细胞凋亡机制 SMZL涉及的突变基因还有部分与染色体重塑相关,主要有MLL2、ARID1A、CREBBP、EP300、TBL1XR1基因等[9]。MLL2是组蛋白甲基转移酶编码基因,通过影响染色质的结构而调控基因的转录表达,在SMZL患者中的突变率为11%~15%,但在FL患者中可高达89%[35]。ARID1A是SWI/SNF染色体重构家族中的一员,它能通过能量动员核小体使染色质重构,从而调节细胞周期相关基因及干细胞自我更新等靶基因的转录,ARID1A在SMZL患者中的突变率仅为6%~10%[9]。 TP53基因是重要的抑癌基因,其编码的p53蛋白能够保持细胞内基因的稳定性,并调节细胞的增殖、分化和凋亡。TP53缺失可见于13%~15%的SMZL患者,目前主要认为TP53缺失是SMZL的继发突变,预示着患者预后较差[10]。 五、表观遗传学及MicroRNA(miRNA) 表观遗传学异常会使基因错误表达,引起代谢紊乱和肿瘤的发生。Arribas等[36]通过全基因组启动子甲基化水平分析,将98例SMZL分成高甲基化组(21%)和低甲基化组(79%),发现启动子的高甲基化状态多与IGHV1-2重排、NOTCH2突变、7q31-32缺失、向DLBCL转化等遗传生物学特性共同发生,可以定义为SMZL的一个特殊的表观遗传学亚组。体外实验发现用去甲基化药物可以使部分抑癌基因重新进入低甲基化状态并再次表达,高甲基化组尤其受益。进一步证明了甲基化水平在SMZL的发生中起一定作用。 miRNA可识别靶mRNA并调节其翻译表达,在调节细胞分化、增殖和凋亡中起关键作用。miRNA谱分析发现在SMZL中有51个miRNA表达失调,其中miRNA155、miRNA21、miRNA34a、miRNA193b明显高表达,miRNA27b、miRNA145等低表达。miRNA155、miRNA21靶基因分别是PLEKHG5、TSPYL5,这两种miRNA具有原癌基因的潜能,导致NF-κB通路的异常激活[37],在其他B细胞淋巴瘤中也有发现。而miRNA34a、193b的靶基因是TNFAIP1,TNFAIP1可以通过抑制Bcl-1表达等机制来诱导细胞凋亡[38]。miRNA27b的低表达可以使RHOH和AIM2两个原癌基因表达活性增高,而miRNA145的低表达可以使淋巴瘤相关的整合素CD40表达上调。这些异常表达miRNA分布在不同的染色体区域,并不能用SMZL常见的细胞遗传学异常来解释。这种特征性miRNA表达谱异常在其他几项小样本分析中也被证实[39]–[40],可能与SMZL发生有一定关系。 六、结语 综上,基于SMZL的可能发病机制。已有的研究结果显示,IgHV1-2*04使用、7q32缺失、3q扩增、NOTCH2和KLF2基因突变在SMZL患者中的重现性较高,有希望成为提示疾病本质特征的分子标志物,然而其预后意义还有待于进一步研究。同时NOTCH2、NF-κB、BCR和TLR通路在SMZL发生、发展中起重要作用。对SMZL分子发病机制和遗传学背景的研究有助于更好地了解SMZL的生物学特性,为指导靶向治疗提供新的思路。

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          The coding genome of splenic marginal zone lymphoma: activation of NOTCH2 and other pathways regulating marginal zone development

          Splenic marginal zone (MZ) lymphoma (SMZL) is a neoplasm of mature B cells that affects elderly patients and involves the spleen, bone marrow, and peripheral blood, while typically sparing peripheral lymph nodes and other sites populated by MZ B cells, namely mucosa-associated lymphoid tissue sites (Matutes et al., 2008; Swerdlow et al., 2008; Traverse-Glehen et al., 2011). Within the spleen, tumor cells are represented by small lymphocytes that occupy the MZ surrounding germinal centers and infiltrate the red pulp (Swerdlow et al., 2008). Despite an indolent behavior in the majority of patients, ∼25% of SMZL patients experience a progressive course leading to early death (Matutes et al., 2008; Salido et al., 2010). The pathogenesis of SMZL is currently elusive. Clinical and epidemiological data point to an association with hepatitis C virus (HCV); however, the infection rate in SMZL patients does not exceed ∼15%, even in geographic areas in which the virus is endemic (Hermine et al., 2002; Suarez et al., 2006). The contribution of antigen stimulation to SMZL pathogenesis is suggested by the highly restricted immunoglobulin gene repertoire, including selective usage of the immunoglobulin heavy chain variable (IGHV) 1-2*04 allele in ∼20–30% of cases, but the relevant antigen has not been identified (Warsame et al., 2011; Bikos et al., 2012). Although the molecular pathogenesis of many lymphoma entities has been elucidated in detail (Swerdlow et al., 2008), relatively little is known about the genetic lesions associated with SMZL. Deletions of 7q31-q32 and gains of 3q are recurrent in ∼20–30% and ∼10–20% of cases, respectively, but the genes targeted by these lesions are unknown (Salido et al., 2010; Watkins et al., 2010; Rinaldi et al., 2011; Robledo et al., 2011). Cancer genes known to harbor genetic lesions in SMZL are not specific for this lymphoma type, and are limited to TP53, which is disrupted in ∼15% of cases, most likely as a secondary genetic alteration (Gruszka-Westwood et al., 2001; Salido et al., 2010; Rinaldi et al., 2011), and to genes of the NF-κB pathway, which are mutated in ∼30% of cases (Rossi et al., 2011; Yan et al., 2012). Scant knowledge of somatic gene lesions associated with SMZL limits the present understanding of its pathogenesis and hampers the possibility of diagnosis and classification based on genetics, one of the mainstay criteria adopted by the World Health Organization Classification of Tumours of Hematopoietic and Lymphoid Tissues for the diagnosis of B cell lymphoma (Swerdlow et al., 2008). By integrating whole-exome sequencing and genome-wide high-density single nucleotide polymorphism (SNP) array data, this study identifies alterations of key regulators of MZ development in ∼60% of SMZL patients, with NOTCH2 representing the most frequently mutated gene in this lymphoma type. RESULTS Identification of recurrent targets of genetic alterations in SMZL To discover somatic, nonsilent mutations and copy number aberrations (CNAs) that are clonally represented in the SMZL coding genome, and presumably contributed to the initial expansion of the tumor clone, we performed massively parallel sequencing and high-density SNP array analysis of paired tumor and normal DNA from eight untreated individuals diagnosed with SMZL (Table S1). After enrichment of protein-coding genes by a hybridization-capture method, next-generation sequencing was performed using the Illumina HiSeq2000 instrument (Table S2). The whole-exome sequencing approach allowed us to map an average of ∼102.5 million reads per sample at a mean depth of 110.6× (range, 59.0-137.0× per sample), with an average of 83.3% of the target sequence being covered by at least 30 reads (range, 72.0–86.0%; Table S2). Bioinformatic analysis followed by Sanger resequencing validation confirmed the presence of 203 somatic, nonsilent mutations (mean, 25.3/case; range, 12–44/case), affecting 191 distinct genes (validation rate, 92.6%; Fig. 1, A–D, and Table S3). The relative expression of the variant allele was determined by transcriptome analysis, performed in 6 of the 8 cases (Table S3). Figure 1. SMZL coding genome complexity. (a) Number and type of nonsilent mutations identified in the 8 discovery genomes. (b) The pattern of nucleotide substitutions in the discovery genomes revealed a predominance of transitions over transversions (121:67, ratio of 1.8) and a preferential targeting of G and C nucleotides (66.0% affecting G/C compared with 34.0% affecting A/T nucleotides). (c) Mutation frequency at specific dinucleotides (red bars). A significant bias toward alterations at 5′-CpG-3′ dinucleotides, which accounted for 15.4% of all missense and nonsense changes, was documented. The expected frequencies (gray bars) correspond to the dinucleotide sequence composition of the Consensus CDS. Asterisks denote statistically significant differences in overrepresented changes, as assessed by a Poisson distribution after correction for multiple hypotheses. (d) Fraction of sequencing reads reporting individual somatic nonsilent variants (gray circles) in the discovery genomes. The large majority of the nonsilent mutations (82.1%) were present in at least 20% of the reads. (e) Overall number and frequency of somatically acquired CNAs. Losses of whole chromosomal arms were not observed and are thus not reported in the figure. (f) Combined load of somatically acquired genetic lesions in the discovery genomes, including nonsilent mutations and CNAs. By using the Affymetrix SNP6.0 platform, 41 somatic CNAs (30 deletions and 11 gains) were identified in the 8 discovery SMZL cases (mean, 5.1/case; range, 0–19/case; Fig. 1 E and Table S4). Alterations known to be associated with SMZL (3q gain, 7q31-q32 deletion, 17p deletion) and previously detected by FISH were correctly identified using the SNP array approach. Of the 41 CNAs, 8 (7 losses and 1 gain) were defined as focal, i.e., spanning ≤3 genes, with none being recurrently observed. When combining point mutations and CNAs, the overall load of tumor-acquired lesions was heterogeneous across the 8 SMZL cases investigated, ranging from 13–60 lesions/case (mean load, 30.5 lesions/case; Fig. 1 F). Genes identified through the whole-exome sequencing and high-resolution SNP array approaches were prioritized for further assessment of their mutation frequency according to the fulfillment of one or more of the following criteria: (a) mutation recurrence in the discovery panel; (b) involvement by both point mutations and focal copy number changes or truncating deletions; and (c) involvement in cellular pathways known a priori to be potentially relevant for SMZL biology. The analysis was also extended to selected genes that were either involved in the same pathways as the genes found to be altered in the discovery genomes (n = 7, including NOTCH1, FBXW7, SPEN, PTEN, CTNNB1, CD79A, and CD79B) and/or those previously implicated in SMZL pathogenesis (n = 7, including IKBKB, TNFAIP3, TRAF3, MAP3K14, TP53, CARD11, and MYD88; Rossi et al., 2011; Yan et al., 2012), even if they were not identified in the discovery phase. Based on these criteria, 61 genes (47 revealed by the genomic approach in the discovery panel, and 14 involved in the same pathways as genes mutated in the discovery genome) were analyzed by Sanger-based resequencing of their coding exons and consensus splice sites in an independent screening panel of 32 SMZL cases (Table S5); for selected genes, an additional extension panel of 77 SMZL cases was also analyzed (Table S6; total number of cases, 109). Of the 61 genes investigated, 21 were found to be mutated in at least two SMZL cases, and 18 were altered in ≥5% of cases. Overall, the genes that are recurrently mutated in SMZL point to the involvement of specific programs implicated in normal MZ development (NOTCH, NF-κB, B cell receptor, and Toll-like receptor signaling), as well as in chromatin remodeling and transcriptional regulation. Alterations of NOTCH2 A molecular feature of SMZL revealed by this study is the presence of recurrent lesions in genes encoding for components of the NOTCH signaling pathway, a master regulator of normal MZ development (Kuroda et al., 2003; Saito et al., 2003; Moran et al., 2007; Santos et al., 2007; Pillai and Cariappa, 2009; Hampel et al., 2011). Targeted resequencing of NOTCH2, a gene required for MZ B cell differentiation (Saito et al., 2003; Moran et al., 2007; Pillai and Cariappa, 2009; Hampel et al., 2011), showed recurrent mutations in 25/117 (21.3%) SMZLs, including 2/8 (25.0%) discovery cases and 23/109 (21.1%) cases from the screening/extension panels. These data establish NOTCH2 as the most frequently mutated gene in SMZL (Fig. 2). Figure 2. Recurrently targeted pathways in SMZL. Percentage of SMZL cases harboring mutations in selected genes belonging to cellular pathways that are recurrently altered in SMZL. Numbers at the bottom indicate the actual number of mutated cases over the total samples analyzed. Asterisks denote genes that are also implicated in Toll-like receptor responses. BCR, B cell receptor. NOTCH2 mutations were represented in all instances by truncating events (14 frameshift indels and 11 nonsense mutations), and clustered within a hotspot region in exon 34, including a recurrent p.R2400* nonsense mutation in 6/25 (24.0%) cases (Fig. 3 A, Tables S3, and Table S7). NOTCH2 mutations were consistently absent in the heterodimerization domain or in other portions of the gene that are targeted by inactivating mutations in different cancer types (Wang et al., 2011b). Based on their distribution, all mutations were predicted to cause impaired degradation of the NOTCH2 protein through the elimination or truncation of the C-terminal PEST domain (Fig. 3 A). Analysis of paired normal DNA confirmed the somatic origin of the mutations in all cases for which material was available (n = 13). NOTCH2 mutations were present in ∼40% of the reads by transcriptome sequencing, indicating allelic balance in the expression of the WT and mutated allele (Table S3). Western blot analysis of NOTCH2 expression consitently revealed the presence of an aberrant band of lower molecular weight, corresponding in size to the predicted truncated NOTCH2 protein, in all mutated cases studied (Fig. 4). Copy number gains of NOTCH2 were never observed in 110 SMZL cases analyzed by SNP array and/or FISH analysis. Figure 3. NOTCH2 is frequently mutated in SMZL. (a) Schematic representation of the human NOTCH2 gene (bottom) and protein (top), with its key functional domains (EGF, epithelial growth factor; LNR, LIN-12/NOTCH repeats; HD, heterodimerization; TM, transmembrane; RAM, regulation of amino acid metabolism; TAD, transactivation domain). Color-coded symbols indicate the type and position of the mutations. (b) Prevalence of NOTCH2 mutations among mature B cell tumors (EMZL, extranodal MZ lymphoma; NMZL, nodal MZ lymphoma; HCL, hairy cell leukemia; CLL, chronic lymphocytic leukemia; MCL, mantle cell lymphoma; FL, follicular lymphoma; MM, multiple myeloma). Numbers on the top indicate the actual number of mutated cases over the total samples analyzed. Figure 4. NOTCH2 expression in SMZL. Western blot analysis of NOTCH2 protein expression in purified primary tumor cells from 5 SMZL cases carrying WT or mutated (M) NOTCH2, and in the SMZL cell line Karpas 1718, also WT for NOTCH2 (left); the specificity of the antibody was validated by using the BJAB cell line, which lacks NOTCH2 mRNA expression (right; asterisk indicates nonspecific band). Arrow indicates the intact NOTCH2 protein; a band of lower molecular weight, consistent with the predicted size of the NOTCH2 protein encoded by the mutant allele, can be detected in all NOTCH2-mutated patients, but not in NOTCH2 WT samples. Where available, the relative NOTCH2 mRNA levels in the same samples are quantified by qRT-PCR (bottom; na, not available). In 3 patients for which multiple samples were available from different involved organs, the same NOTCH2 mutation was detectable at all sites, namely peripheral blood, bone marrow, and spleen. This observation suggests that the mutation had been acquired before dissemination of the lymphoma clone to multiple anatomical sites. To verify the specificity of NOTCH2 mutations for SMZL, NOTCH2 was investigated across the clinico-pathological spectrum of mature B cell tumors (n = 399). NOTCH2 mutations were consistently absent in nodal MZ lymphoma (0/18), chronic lymphocytic leukemia (0/100), mantle cell lymphoma (0/20), follicular lymphoma (0/20), hairy cell leukemia (0/20), and multiple myeloma (0/22), whereas they occurred sporadically in extranodal MZ lymphoma (1/65, 1.5%) and, in accordance with a previous study (Lee et al., 2009), were restricted to 5/134 (3.7%) diffuse large B cell lymphomas (DLBCL; Fig. 3 B). The clinical impact of NOTCH2 mutations on SMZL overall survival (OS) was assessed in 94 patients with available follow up. Consistent with the indolent behavior of this lymphoma type, the 5-yr OS of the SMZL cohort was 78.1% (95% CI, 67.8–88.4%). At 5 yr, SMZL patients harboring NOTCH2 mutations were characterized by a significantly higher OS probability (93.3%; 95% CI, 80.0–100%) compared with patients harboring a WT NOTCH2 (74.3%; 95% CI, 61.4–87.2%; P = 0.048; Fig. 5). Consistent with the improved OS, cases harboring NOTCH2 mutations displayed a longer progression-free survival (PFS) after first-line treatment compared with NOTCH2 WT patients (5-yr PFS in NOTCH2 mutated patients, 83%; 95% CI, 65.4–100%; 5-yr PFS in NOTCH2 WT patients, 44.1%; 95% CI, 28.9–58.3%; P = 0.020). There were no differences in major adverse events between NOTCH2-mutated and unmutated patients, as documented by a similar treatment-related mortality in the two groups (NOTCH2-mutated patients, 0/18; NOTCH2 WT patients 1/53, 1.8%; P = 1.000). Figure 5. NOTCH2 mutations are associated with better OS. Kaplan-Meier estimates of OS in SMZL patients (n = 94), according to NOTCH2 mutation status. Overall, these data document that, among B cell neoplasia, NOTCH2-activating mutations are predominantly associated with SMZL, and underscore the genetic individuality of SMZL versus other MZ-derived lymphomas and versus indolent B cell lymphoproliferative disorders clinically mimicking SMZL. Alterations in other genes of the NOTCH pathway In addition to NOTCH2, other genes involved in NOTCH signaling and known to be relevant for normal MZ differentiation were affected by genomic lesions in SMZL, including NOTCH1, SPEN, and DTX1 (Fig. 2; Kuroda et al., 2003; Saito et al., 2003; Santos et al., 2007; Pillai and Cariappa, 2009). NOTCH1, a paralogue of NOTCH2 implicated in several phases of lymphoid development, including terminal B cell differentiation into immunoglobulin-secreting cells (Santos et al., 2007; Yuan et al., 2010), was affected in 6/117 (5.1%) SMZLs by a recurrent 2-bp deletion (p.P2515fs*4) that truncates the PEST domain, similar to NOTCH2 lesions (Fig. 6 A and Table S7). This deletion also represents the most common NOTCH1 alteration in chronic lymphocytic leukemia and mantle cell lymphoma (Fabbri et al., 2011; Wang et al., 2011a; Kridel et al., 2012; Quesada et al., 2012; Rossi et al., 2012), and the most recurrent NOTCH1 PEST domain mutation in T cell acute lymphoblastic leukemia, where it causes impaired degradation of the NOTCH1 protein (Weng et al., 2004). Figure 6. Mutations of genes belonging to the NOTCH, migration/adhesion, NF-κB, and B cell receptor pathways in SMZL. Schematic diagram of the proteins targeted by mutations in SMZL, with their key functional domains (a, NOTCH pathway; b, NF-κB pathway). Symbols indicate the type of mutation. SPEN, also known as MINT, has been reported to repress NOTCH signaling by physically interacting with and causing inhibition of the transcription factor RBPJ, which is implicated in the NOTCH signaling cascade (Kuroda et al., 2003; Li et al., 2005; VanderWielen et al., 2011). Consistent with its biochemical function, SPEN physiologically acts in the immune system as a negative regulator of B lymphocyte differentiation into MZ B cells by counteracting NOTCH activation (Kuroda et al., 2003). SPEN was found to be mutated in 6/117 (5.1%) SMZL cases (Fig. 2). With one exception, SPEN mutations were represented by inactivating events, including three frameshift indels and two nonsense substitutions (Fig. 6 A and Table S7), which were documented to be of somatic origin in all cases with available paired normal DNA. SPEN-mutated alleles were predicted to encode truncated proteins lacking the C-terminal domain involved in the interaction of SPEN with RBPJ, and to be necessary for NOTCH signaling inhibition (Fig. 6 A; Kuroda et al., 2003). In addition to truncating mutations, SPEN was affected by one somatic missense substitution, categorized as probably damaging by PolyPhen-2 (Fig. 6 A and Table S7), and by four monoallelic deletions (Table S8). In all evaluable cases, SPEN mutations were restricted to a single allele and were not accompanied by deletions of the second allele. This pattern of predominant monoallelic inactivation is in agreement with in vitro models, suggesting that SPEN mutants may exert a dominant-negative effect (Li et al., 2005). DTX1 encodes a RING finger ubiquitin ligase that binds the NOTCH family proteins and modulates their signaling, is highly expressed in MZ B cells, and may be important for late steps of B cell differentiation (Izon et al., 2002; Saito et al., 2003). In 2/117 (1.7%) SMZLs, DTX1 was affected by somatically acquired missense substitutions mapping within two functionally relevant domains: the WWE1 domain, which mediates physical interactions between DTX1 and NOTCH (Zweifel et al., 2005), and the proline-rich domain, which may serve as a docking site for NOTCH inhibitory factors (Matsuno et al., 2002; Fig. 6 A; Tables S3 and S7). In summary, ∼32% (37/117) of SMZL patients carry alterations of genes belonging to the NOTCH pathway, with NOTCH2 mutations accounting for approximately 2/3 of the events (25/37; 67.5%; Fig. 7). Figure 7. Mutually exclusive involvement of genes implicated in MZ development. In the heatmap, rows correspond to genes and columns represent individual patients. Color coding is based on gene mutation status (white, WT; red, mutated). Asterisks denote genes that also modulate Toll-like receptor responses. BCR, B cell receptor. Alteration of additional pathways involved in MZ development Besides NOTCH signaling, the development of a normal MZ requires B cell migration to and retention within the spleen marginal sinus until they are activated (Pillai and Cariappa, 2009). SWAP70 encodes for an F-actin–binding/Rho GTPase–interacting protein that is necessary for normal B cell trafficking across spleen compartments (Chopin et al., 2010a, 2011). In 4/117 (3.4%) cases, SWAP70 was disrupted by truncating mutations that removed the C-terminal domain of the protein required for binding to F-actin (Fig. 6 A; Tables S3 and S7). SWAP70 was also affected by a monoallelic deletion in one additional SMZL (Table S4). Moreover, one SMZL (0.9%) displayed a somatic mutation in the EGR1 B cell transcription factor, which also plays a role in MZ development (Table S3; Gururajan et al., 2008). EGR2, a paralogue of EGR1, was somatically mutated in one additional case (0.9%; Table S3). Active NF-κB signaling is necessary for the generation and/or maintenance of normal MZ B cells (Calado et al., 2010; Chu et al., 2011; Conze et al., 2010; Pappu and Lin, 2006; Moran et al., 2007; Xie et al., 2007; Sasaki et al., 2008; Pillai and Cariappa, 2009). Mutations of both the canonical (17/117, 14.5% cases) and noncanonical (11/117, 9.4% cases) NF-κB pathways were recurrent in SMZL (Fig. 2), and affected several previously identified genes in this lymphoma type (Rossi et al., 2011; Yan et al., 2012), including IKBKB (8/117, 6.8%), TNFAIP3 (8/117, 6.8%), BIRC3 (6/117, 5.1%), TRAF3 (4/117, 3.4%), and MAP3K14 (1/117, 0.9%; Fig. 6 B; Table S3 and Table S7). These genes were also targeted by CNAs, including deletions of TNFAIP3 (8/110, 7.2%), BIRC3 (7/110, 6.3%), and TRAF3 (6/110, 5.4%), and gains of MAP3K14 (7/110, 6.3%; Table S8). In addition to genes specifically attributed to the NF-κB pathway, recurrent mutations were also found in CARD11 and MYD88, which, among their many functions, act as positive regulators of NF-κB in signaling from the B cell receptor and Toll-like receptor, respectively (Fig. 2; Lenz et al., 2008; Ngo et al., 2011). CARD11 mutations (6 missense and 2 in frame deletions) cluster within the coiled-coil domain in 8/117 (6.8%) cases (Fig. 6 B and Table S7). In 6/117 (5.1%) SMZLs, MYD88 was targeted by a recurrent missense substitution (p.L265P) that has been previously reported in activated B cell–type DLBCL (Fig. 6 B and Table S7; Ngo et al., 2011). Cases harboring NF-κB pathway mutations and cases harboring NOTCH pathway mutations did not differ in terms of clinical and biological features at presentation, including age, sex, performance status, levels of hemoglobin, LDH, β-2-microglobulin and albumin, HCV infection, IGHV mutation status, usage of the IGHV1-2*04 allele, stereotyped VH CDR3, 7q31-q32 deletion, 3q gain, or TP53 disruption (P > 0.05 in all instances). Overall, mutations of positive and negative NF-κB regulators accounted for 40/117 (34.1%) SMZL cases (Fig. 7), implicating activation of NF-κB as a major contributor to the pathogenesis of this disease. Alteration of genes involved in chromatin remodeling and transcriptional regulation Apart from genes implicated in MZ development, whole-exome sequencing revealed a second set of genes recurrently mutated in SMZL and regulating chromatin remodeling (Fig. 2). The MLL2 histone methyltransferase controls gene transcription by modifying the lysine-4 position of histone 3 and is recurrently mutated in FL and DLBCL (Morin et al., 2011; Pasqualucci et al., 2011b). Inactivating mutations of MLL2 occurred in 6/40 (15.0%) SMZLs (Fig. 8; Tables S3 and S7), leading to removal or truncation of the C-terminal SET domain required for its enzymatic activity. In addition, two SMZLs showed a p.P692T somatic missense substitution. ARID1A, a member of the SWI-SNF chromatin remodeling family that was reported as mutated in several solid tumors (Wiegand et al., 2010), was targeted by genetic lesions in 4/40 (10.0%) cases, including 2 point mutations and 2 deletions (Fig. 8; Tables S3, S7 and S8). EP300 and CREBBP are two highly related acetyltransferases that are also recurrently disrupted in B cell lymphoma (Pasqualucci et al., 2011a) and acute lymphoblastic leukemia (Mullighan et al., 2011). Somatic missense mutations of EP300 were found in 2/40 (5%) SMZL cases (Fig. 8 and Table S3), whereas one additional patient harbored a small deletion that juxtaposes in-frame the first 16 exons of CREBBP to the C-terminal portion of the ZNF434 gene, thus abrogating the CREBBP acetyltransferase domain, as confirmed by transcriptome sequencing analysis (not depicted). Somatic mutations of SIN3A, encoding for a core component of the SIN3–HDAC1/2 histone deacetylase complex, occurred in 3/40 (7.5%) SMZLs, and, in two cases, targeted regions that are required for the recruitment of histone modification complexes (Fig. 8; Tables S3 and S7; Grzenda et al., 2009). Other genes involved in chromatin remodeling and found to be somatically mutated in single SMZL cases are represented in Fig. 2. Figure 8. Mutations of genes involved in chromatin remodeling and transcriptional regulation. Schematic diagram of the indicated proteins, with their key functional domains. Symbols indicate the type of mutation. Mutations were also detected in other transcriptional regulators. TBL1XR1, an intrinsic component of the SMRT-N-CoR transcription co-repressor machinery that was recently found to be recurrently disrupted in B cell tumors (Perissi et al., 2008), showed mutations in 4/40 (10.0%) SMZLs (Fig. 2). Mutations (two frameshift deletions and three somatically acquired missense substitutions) targeted the protein WD domains implicated in the exchange of nuclear receptor co-repressors for co-activators (Fig. 8; Table S3 and Table S7; Oberoi et al., 2011). TBL1XR1 mutations were monoallelic in three cases, whereas one case harbored a disrupting mutation coupled to a missense substitution (Table S7). Three additional SMZLs showed monoallelic TBL1XR1 deletion (Table S8). GPS2, another member of the SMRT-N-CoR transcription co-repressor machinery that physically interacts with TBL1XR1 (Oberoi et al., 2011), was biallelically inactivated in one SMZL by a nonsense mutation with deletion of the second allele (Table S3 and Table S4). The mutation targeted the GPS2 domain required for TBL1XR1 interaction. Monoallelic deletions of GPS2 were observed in additional eight cases (Table S8). Overall, mutations of chromatin remodeling and transcriptional regulation genes occurred in 14/40 (35.0%) SMZLs and, as observed in other cancer types (Gui et al., 2011), were frequently concurrent in the same patient (∼50% of the mutations; Fig. 9), suggesting that they cooperate to promote tumorigenesis. Figure 9. Integrated analysis of mutations affecting chromatin remodeling genes in SMZL. In the heatmaps, rows correspond to mutated genes and columns represent individual patients. Color coding is based on gene mutation status (white, WT; red, mutated). Analysis of chromatin remodeling genes was extended to the screening panel only (in total, 40 cases), and is thus shown separately. Mutations of genes regulating MZ development and NF-κB activation characterize ∼60% of SMZLs Given the biological heterogeneity of SMZLs, we investigated the relationship between mutations of genes controlling MZ development and established genetic, immunogenetic, and biological subgroups of SMZLs, including those defined by deletion of 7q31-q32 (21/110, 19.1%), 3q gain (14/110, 12.7%), expression of unmutated IGHV genes (29/110, 26.3%), usage of the IGHV1-2*04 allele (26/110, 23.6%), usage of stereotyped VH CDR3 (9/110, 8.1%), positive HCV serology (11/86, 12.7%), and TP53 mutations (17/117, 14.5%). This analysis did not disclose any selective association, suggesting that mutations of genes controlling MZ development play an independent role in lymphomagenesis (Table S9). A preferential, though not selective, association was observed between deletion of 7q31-q32, a cytogenetic abnormality characteristic of SMZL, and cases harboring mutations of MZ development genes (19/64, 29.7% in cases harboring mutations vs. 2/46, 4.3% in cases devoid of mutations; P = 0.001; Table S9). In particular, deletion of 7q31-q32 significantly associated with SMZL harboring NOTCH2 mutations (11/24, 45.8%; P = 0.001). Mutations of genes implicated in MZ development (NOTCH, NF-κB, B cell receptor, and Toll-like receptor pathway, as well as SWAP70, EGR1, EGR2; Izon et al., 2002; Kuroda et al., 2003; Saito et al., 2003; Moran et al., 2007; Santos et al., 2007; Gururajan et al., 2008; Pillai and Cariappa, 2009; Chopin et al., 2010b, 2011; Hampel et al., 2011) show a largely mutually exclusive distribution pattern, although the number of cases (n = 117) lacks statistical power for this type of analysis (Fig. 7). Collectively, these lesions account for the majority of SMZL cases (70/117; 59.8%), and suggest that alterations in genes affecting B cell fate decision toward MZ differentiation represent alternative mechanisms converging on the deregulation of a common downstream target, which may include NF-κB. DISCUSSION One goal of this study was to provide initial information on the landscape of somatic genetic lesions (type and frequency) that characterize the SMZL coding genome. Given the presence of ∼25 nonsilent mutations and ∼5 CNAs per case (on average, ∼30 alterations/case), SMZL appears to show a degree of genomic complexity that is intermediate between that of aggressive lymphoma, namely DLBCL (∼90 nonsilent mutations per case; Morin et al., 2011; Pasqualucci et al., 2011b; Lohr et al., 2012), and that of previously untreated chronic lymphocytic leukemia (∼12 nonsilent mutations per case; Fabbri et al., 2011; Quesada et al., 2012), which shares an indolent course with SMZL. A second key finding of this study was the identification of alterations in genes affecting B cell fate decision toward MZ differentiation as significantly associated with SMZL. Alterations in genes of the NOTCH pathway emerged as highly recurrent (∼30%) in SMZL, with NOTCH2, a key regulator of MZ development, being the most frequently mutated gene (∼20%). All NOTCH2 mutations observed in SMZL cause disruption of the protein inhibitory PEST domain and are predicted to activate NOTCH2 signaling (Lee et al., 2009). Because of the lack of xenograft and cell line models of SMZL, we are currently unable to assess whether these mutations confer ligand independence, or whether the mutated proteins still require activation by ligand binding. Disruption of the PEST domain renders SMZL-associated mutations of NOTCH2 analogous to those involving NOTCH1 in chronic lymphocytic leukemia and mantle cell lymphoma, and to a subset of NOTCH1 mutations in T cell acute lymphoblastic leukemia (Fabbri et al., 2011; Wang et al., 2011a; Kridel et al., 2012; Quesada et al., 2012). Nevertheless, NOTCH2 mutations appear to be relatively specific for SMZL, being virtually absent in other major types of mature B cell neoplasia and rare in DLBCL (Lee et al., 2009). Consistent with our findings, one single mutation of NOTCH2 was recently described in one case of SMZL (Trøen et al., 2008). In addition to NOTCH2, other modulators or members of the NOTCH pathway were targeted by genetic lesions in SMZL, including SPEN, DTX1, and NOTCH1. The alternative involvement of multiple genes converging on the NOTCH pathway, together with the well-established functional role of some of these alterations, namely NOTCH1 mutations in T cell acute lymphoblastic leukemia (Weng et al., 2004), strongly support their pathogenic role in SMZL. As is the case for most cancer-associated genetic lesions, activation of NOTCH2 may not be sufficient for malignant transformation. In fact, patients affected by the Hajdu-Cheney syndrome, an autosomal-dominant genetic disease that causes severe and progressive bone loss and is associated with germline NOTCH2 mutations analogous to those identified in SMZL, do not develop lymphomas (Brennan and Pauli, 2001; Simpson et al., 2011). Similarly, transgenic mice engineered to express activating NOTCH2 mutations in mature B cells display an expansion of the MZ at the expense of the follicular compartment, but do not develop lymphoma (Hampel et al., 2011). It is important to note, however, that lymphoma development may require longer times than those observed so far both in Hajdu-Cheney patients (no diagnosed individual was >50 yr old; Brennan and Pauli, 2001; Simpson et al., 2011) and in mice (1 yr), consistent with the elderly age and indolent course of SMZL (Hampel et al., 2011). Collectively, the genetic alterations associated with SMZL appear to predominantly involve signaling pathways that regulate MZ development, including: (a) NOTCH, via the alternative mutation of multiple genes (NOTCH2, NOTCH1, SPEN, and DTX1); (b) NF-κB, via mutation of TNFAIP/A20, BIRC3, TRAF3 and CARD11; and (c) the B cell receptor, via mutation of CARD11. Indeed, at least in mice, the commitment of mature B cells to the MZ compartment requires signaling from NOTCH2 (Kuroda et al., 2003; Saito et al., 2003; Moran et al., 2007; Santos et al., 2007; Pillai and Cariappa, 2009; Hampel et al., 2011), as well as activation of the NF-κB transcription complex (Xie et al., 2007; Sasaki et al., 2008; Calado et al., 2010; Conze et al., 2010; Chu et al., 2011) and possibly antigen stimulation through the B cell receptor and Toll-like receptor (Pappu and Lin, 2006). The alteration of genes implicated in the physical retention of MZ B cells within the spleen might also be important for SMZL pathogenesis, as suggested by the observation of recurrent mutations in SWAP70 (Chopin et al., 2010a, 2011). Thus, the finding that ∼60% of SMZL cases display the alternative deregulation of these pathways suggests that one major component of SMZL pathogenesis is the constitutive activation of signals normally deputed to the differentiation and homing of B cells into the MZ. Finally, the results herein have important implications for the clinical management of SMZL. Because the differential diagnosis of SMZL from other indolent B cell lymphoproliferative disorders clinically mimicking SMZL is often complex (Matutes et al., 2008; Swerdlow et al., 2008), some of the genetic alterations reported here, specifically mutations of NOTCH2, may serve as potentially helpful markers. More importantly, the results of this study provide a rationale for the design of novel therapeutic strategies for SMZL, which, to date, remains a disease orphan of specifically targeted drugs (Traverse-Glehen et al., 2011). New regimens may be useful to avoid splenectomy, a well-established therapeutic option in SMZL, which has perioperative and long-term morbidity and mortality, especially in elderly or unfit individuals (Matutes et al., 2008). The NOTCH pathway, which we show is affected by genetic lesions in up to 30% of SMZLs, may represent an attractive candidate therapeutic target, as some NOTCH inhibitors, such as those preventing its enzymatic conversion to active transcription factor, are already available, and others are under active clinical development (Real et al., 2009). The NF-κB pathway represents an additional potential target; available proteasome inhibitors already approved for other malignancies, or more specific anti–NF-κB compounds currently under development, should be tested for their efficacy in SMZL, either alone or in combination with NOTCH inhibitors. MATERIALS AND METHODS Patients and tumor biopsies. The study panel comprised a total of 117 SMZL samples obtained from frozen spleen biopsies of newly diagnosed, previously untreated patients, and was distinguished into a discovery panel (n = 8 cases), a screening panel (n = 32 cases), and an extension panel (n = 77 cases). Out of the 109 SMZLs used as screening and extension panel, 61 were already reported (Rossi et al., 2011). In all cases, the SMZL diagnosis was based on spleen histology and was confirmed by centralized pathological revision (S.A. Pileri). Consistent with a SMZL diagnosis, all cases of the discovery and screening panels lacked the t(11;18) and the t(14;18) translocations (Matutes et al., 2008), and all 117 cases lacked the BRAF p.V600E mutation (Swerdlow et al., 2008; Tiacci et al., 2012). Matched normal DNA was obtained from saliva or peripheral blood granulocytes in 48 patients (n = 8 discovery cases and 40 cases from the screening and extension panel). The clinical and biological characteristics of cases belonging to the SMZL discovery, screening, and extension panels are summarized in Tables S1, S5, and S6, respectively. For comparative purposes, 399 B cell tumors other than SMZL were also included in the study (18 nodal MZ lymphomas, 65 extranodal MZ lymphomas, 100 chronic lymphocytic leukemias, 20 mantle cell lymphomas, 20 follicular lymphomas, 134 DLBCLs, 20 BRAF p.V600E mutation-positive hairy cell leukemias, and 22 multiple myelomas). All of the 399 samples had been obtained at diagnosis from the involved site (lymph nodes or extranodal sites in the case of lymphoma; CD138+ cells purified from bone marrow aspirates in the case of multiple myeloma; peripheral blood purified B cells in the case of hairy cell leukemia; and peripheral blood mononuclear cells in the case of chronic lymphocytic leukemia). The number of mature B cell neoplasms included in each panel was estimated to allow a 90% probability of identifying genes that are mutated in at least 10% of cases. Patients provided informed consent in accordance with local IRB requirements and The Declaration of Helsinki. The study was approved by the Ethical Committee of the Ospedale Maggiore della Carità di Novara affiliated with the Amedeo Avogadro University of Eastern Piedmont (Protocol Code 59/CE; Study Number CE 8/11) and by the Institutional Review Board of Columbia University. DNA extraction. High molecular weight (HMW) genomic DNA was extracted from tumor and normal samples according to standard procedures (Rossi et al., 2011). In all tumor cases, the fraction of tumor cells in the tissue biopsy section used for molecular studies was estimated to be >70% by morphology, immunohistochemistry, and/or flow cytometry. DNA was quantified by the Quant-iT PicoGreen reagent (Invitrogen) in the discovery panel, and by the NanoDrop 2000C spectrophotometer (Thermo Fisher Scientific) in the screening and extension panels. All DNA samples were verified for integrity by 1% agarose gel electrophoresis. Tumor cell clonality was established by amplification of the rearranged IGH genes, as described in detail in the paragraph “IGHV-IGHD-IGHJ rearrangement analysis.” Analysis of patient-specific IGHV-IGHD-IGHJ rearrangements were also performed in the paired normal DNA to exclude contamination from tumor cells. Whole-exome capture and massively parallel sequencing. Purified tumor and germline genomic DNA (3 µg) from the 8 discovery SMZL cases was enriched in protein coding sequences using the in-solution exome capture SureSelect Human All Exon 50Mb kit (Agilent Technologies), according to the manufacturer’s protocol. The SureSelect Human All Exon 50 Mb kit encompasses all coding exons annotated by the GENCODE project, including all exons in the Consensus CDS (CCDS, March 2009) database, 10 bp of flanking sequence for each targeted region, and small noncoding RNAs from miRBase (v.13) and Rfam. The captured targets were subjected to massively parallel sequencing using the Illumina HiSeq 2000 analyzer (Illumina) with the paired-end 2 × 100 bp read option, following the manufacturer’s instructions. As quality controls for the precapture and post-capture steps, randomly selected PCR-amplified clones of the PCR products were subjected to Sanger sequencing to verify their preferential alignment to human genomic regions and to human coding transcripts (n = 50/library). Exome capture and massively parallel sequencing were performed at the HiSeq Service of Fasteris SA (Plan-les-Ouates, Switzerland). Sequence mapping and identification of tumor-specific variants. Paired-end reads (∼102.5 million per case) obtained by high-throughput sequencing were aligned to the human genome reference hg19/NCBI GRCh37 using the BWA alignment tool version 0.5.9, and provided a mean depth of 111x with at least 83% of the target exome covered at 30x (Table S2). Sequence variants, i.e., differences from the reference sequence, were identified separately for each tumor and normal sample. The frequency of each variant was estimated from the total number of reads covering the position of that variant. Using the SAVI (Statistical Algorithm for Variant Identification) algorithm developed at Columbia University (Tiacci et al., 2012), an empirical prior was constructed for the variant frequencies. From that prior, we obtained a corresponding high-credibility interval (posterior probability ≥1–10−5) for the frequency of each variant and a high-credibility interval for the corresponding change in frequency between the tumor and the normal samples. 218 nonsilent variants, which are not reported in dbSNP 135 and had high posterior probability (≥1–10−5) of nonzero presence in the tumor, as well as at least 1% change from the normal with high posterior probability (≥1-10−5), were kept for validation by Sanger sequencing. A comparison with data obtained by high-density SNP array analysis of the same tumor/normal pairs established the sensitivity of the method at 96.6% for heterozygous SNP calls and 98% for homozygous SNP calls. Validation of candidate somatic mutations by DNA Sanger sequencing. Candidate nonsilent somatic mutations were subjected to validation by conventional Sanger-based resequencing of PCR products obtained from both tumor and paired normal HMW genomic DNA using primers specific for the exon encompassing the variant. The sequences surrounding the genomic locations of the candidate tumor-specific nonsilent mutations were obtained from the UCSC Human Genome database, and PCR primers were derived from previously published studies (Parsons et al., 2011) or custom-designed using the Primer 3 online software (http://frodo.wi.mit.edu/primer3/). Of the 218 predicted nonsilent variants, 202 (validation rate, 92.6%) were confirmed to be somatic in origin by Sanger sequencing, 6 were also found in the matched normal DNA, thus representing previously nonannotated germline polymorphisms that had not been detected by the high-throughput sequencing analysis, and the remaining 10 variants were absent in both tumor and normal genomic DNA, when tested by Sanger sequencing. Confirmed, somatic nonsynonymous mutations were tested for their functional consequences in silico by using the PolyPhen-2 (Polymorphism Phenotyping) algorithm (http://genetics.bwh.harvard.edu/pph2/), which is based on structure and sequence conservation. Genes found to be mutated were verified for their presence in the Catalogue of Somatic Mutations in Cancer database (Forbes et al., 2011) and in the Cancer Gene Census database. Mutation screening of identified genes. The complete coding sequences and exon–intron junctions of selected genes identified through the whole-exome sequencing and/or the SNP array approach were analyzed in the SMZL screening panel and extension panel by PCR amplification and direct sequencing of whole-genome–amplified DNA obtained using the Repli-g Mini kit (QIAGEN). Sequences for all annotated exons and flanking splice sites were retrieved from the UCSC Human Genome database using the corresponding mRNA accession number as a reference. PCR primers, located ∼50 bp upstream or downstream to target exon boundaries, were either derived from previously published studies (Parsons et al., 2011) or designed in the Primer 3 program and filtered using UCSC in silico PCR to exclude pairs yielding more than a single product. All PCR primers and conditions are available upon request. Purified amplicons were subjected to conventional DNA Sanger sequencing using the ABI PRISM 3100 Genetic Analyzer (Applied Biosystems), and compared with the corresponding germline sequences using the Mutation Surveyor Version 3.97 software package (SoftGenetics) after automated and/or manual curation. Of the evaluated sequences, 99% had a Phred score of ≥20 and 96% had a score of ≥30. Candidate somatic mutations were confirmed from both strands on independent PCR products obtained from HMW genomic DNA. Synonymous mutations, previously reported germline polymorphisms, and changes in the matched normal DNA (when available) were removed from the analysis. The following databases were used to exclude known germline variants in primary cases for which paired normal DNA was not available: Human dbSNP Database at NCBI (build 136), Ensembl Database, the 1000 Genomes Project, five single-genome projects available at the UCSC Genome Bioinformatics resource. High-density SNP array analysis. Copy number abnormalities were assessed by high-density SNP array analysis in 81 of the 117 SMZL cases, including the 8 discovery cases (paired tumor and normal DNA), 21 SMZL from the screening panel (both sets using the Genome-Wide Human SNP Array 6.0; Affymetrix), and 52 SMZL cases from the extension panel (using the GeneChip Human Mapping 250K NspI; Affymetrix; GEO accession no. GSE24881). In brief, HMW genomic DNA was restriction enzyme digested, ligated, PCR amplified, purified, labeled, fragmented, and hybridized to the arrays according to the manufacturer’s instructions. Identification of segments of abnormal copy numbers were performed using the dChipSNP software, and a karyotype-guided normalization procedure according to a published workflow (Pasqualucci et al., 2011b). Whole-transcriptome sequencing (RNA-seq). Whole-transcriptome sequencing was performed in 6 SMZL cases belonging to the discovery panel (cases 12D through 17D). RNA was extracted from CD19+ B cells purified from spleen disaggregation using the Allprep DNA/RNA Mini kit (QIAGEN). Polyadenylated RNA was selected after DNaseI treatment and used as a template for double-stranded cDNA synthesis. The 190–210 bp fraction was then isolated and PCR amplified, and libraries were constructed using the Illumina Genome Analyzer paired-end library protocol according to manufacturer’s instructions. As quality controls for the precapture and postcapture steps, randomly selected PCR-amplified clones of the PCR products were subjected to Sanger sequencing to verify their preferential alignment to human genomic regions and to human coding transcripts (50 clones/library). Transcriptome sequencing was performed at the HiSeq Service of Fasteris SA (Plan-les-Ouates, Switzerland). Whole-transcriptome data analysis. Reads (mean, 17 M per case) obtained by high-throughput sequencing were aligned to a human transcriptome reference (113 M), obtained by stitching together the exons belonging to the RefSeq transcripts as reported at the UCSC Genome Browser, using the BWA alignment tool version 0.5.9. Sequence variants, i.e., differences from the reference sequence, were identified separately for each sample, and credibility intervals for those frequencies, as well as for the change in frequency from the corresponding whole-exome DNA sequencing, were obtained as described in “Sequence mapping and identification of tumor-specific variants.” Expression for each RefSeq transcript was calculated using nonclonal (reads that map to the same exact position are counted once) reads per kilobase of exon model per million mapped reads. For each transcript, we first filter out clonal reads mapping to the same position, and then calculate the mean nonclonal read depth per base and normalize by the total number of nonclonal reads mapped to the transcriptome. IGHV-IGHD-IGHJ rearrangement analysis. PCR amplification of IGHV-IGHD-IGHJ rearrangements was performed on HMW genomic DNA using IGHV leader primers or consensus primers for the IGHV FR1, along with appropriate IGHJ genes, as previously described (Rossi et al., 2011). PCR products were directly sequenced with the ABI PRISM BigDye Terminator v1.1 Ready Reaction Cycle Sequencing kit using the ABI PRISM 3100 Genetic Analyzer (both from Applied Biosystems). Sequences were analyzed using the IMGT databases and the IMGT/V-QUEST tool (version 3.2.17; Centre National de la Recherche Scientifique, LIGM, Université Montpellier 2, Montpellier, France). The following immunogenetic information were recorded for all IGHV-IGHD-IGHJ rearrangements: IGHV gene and allele usage; percentage of identity to the closest germline IGHV allele; VH CDR3 length and composition, including IGHD; and IGHJ gene usage and IGHD gene reading frame. To identify clusters of sequences with common VH CDR3 motifs, sequences were clustered based on the patterns they shared. The VH CDR3 from SMZL was aligned to the VH CDR3 sequences from a database of 28721 samples. Subsets identified as having stereotyped VH CDR3 AA sequences were those characterized by at least 50% amino acid identity and 70% similarity between stereotyped sequences, usage of the same IGHV gene, and identical VH CDR3 length (Bikos et al., 2012). Fluorescence in situ hybridization (FISH). In 36 SMZL cases lacking high resolution SNP array data (11 SMZL cases belonging to the screening panel and 25 SMZL cases from the extension panel) the presence of copy number aberrations in selected candidate genes was assessed by FISH analysis, using the following probes: (a) BAC clones RP11-696E2 (ARID1A), RP11-177O8 (BIRC3), RP11-292B10 (CREBBP), RP11-1078O11 (EP300), RP11-1113D20 (GPS2), RP11-666C2 (MAP3K14), RP11-45L15 (MLL2), RP11-383D9 (PTEN), RP11-622D13 (SPEN), RP11-753H20 (SWAP70), RP11-122K3 and RP11-996H19 (TBL1XR1), RP11-102P5 and RP11-703G8 (TNFAIP3), RP11-676M2 (TRAF3), RP11-1077G19 (WAC); and (b) the commercial probes LSIBCL6 (3q27), LSID7S522-CEP7 (7q31), LSITP53 (17p13.1; Abbott). Labeled BAC probes were tested against normal control metaphases to verify the specificity of the hybridization. For each probe, at least 200 interphase cells with well-delineated fluorescent spots were examined. Nuclei were counterstained with DAPI and antifade reagent, and signals were visualized using a BX51 microscope (Olympus). The presence of copy number abnormalities was scored when the percentage of nuclei showing the abnormality was >10%. Immunoblotting. B cells were purified from the spleen of 3 NOTCH2 WT and 2 NOTCH2-mutated SMZL patients by positive selection, using an anti-CD19 PE antibody, followed by anti-PE microbeads (Miltenyi Biotec). Whole-cell extracts were obtained from CD19-purified SMZL cells or exponentially growing cell lines in RIPA Buffer (140 mM NaCl, 10 mM Tris-HCl, pH 7.5, 0.5% sodium deoxycholate 10x, 0.1% sodium-dodecyl-sulfate + 1% Triton-X 100), according to standard protocols, and proteins were quantified using the Bradford assay. Equivalent amounts of lysates were resolved on 6% SDS-PAGE in reducing conditions. The immunoblot analysis of NOTCH2 expression was performed using a specific anti-NOTCH2 antibody (Bethyl Laboratories) following the manufacturer’s instructions. An anti–rabbit HRP-conjugated antibody (Santa Cruz Biotechnology) was used as a secondary reagent. ERK1/2 (BD) was used as loading control. Image acquisition was performed using the ImageQuant LAS4000 software (GE Healthcare). RNA extraction and quantitative real-time PCR (qRT-PCR). RNA was extracted using RNeasy Plus Mini kit (QIAGEN) and converted to cDNA using the High Capacity cDNA Reverse Transcription kit (Applied Biosystems). qRT-PCR was performed using the 7900 HT Fast Real Time PCR System (SDS2.3 software) using commercial primers (TaqMan Gene Expression Assays; Applied Biosystems). The comparative CT method was used to calculate the expression relative to the endogenous control (Serra et al., 2011). Statistical analysis. OS was measured from date of initial presentation to date of death (event) or last follow-up (censoring). PFS was measured from date of initial presentation to date of disease progression or death as a result of any cause, or last follow-up (censoring). Treatment-related mortality was defined as any deaths reported by investigators as probably/possibly related to SMZL treatment. Survival was analyzed by the Kaplan-Meier method and compared by the log-rank test. Categorical variables were compared by χ2 test and Fisher’s exact test when appropriate. Continuous variables were compared by the t test. All statistical tests were two-sided. Statistical significance was defined as P value < 0.05. The analysis was performed with the Statistical Package for the Social Sciences software v.19. Accession codes. The whole-exome sequencing and copy number data reported in this paper have been deposited in dbGaP under accession no. phs000502.v1.p1 (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000502.v1.p1). Online supplemental material. Table S1 shows the features of the 8 SMZL discovery cases analyzed by whole-exome sequencing. Table S2 reports the results of Illumina sequencing after whole-exome capture. Table S3 reports the validated somatic mutations identified by whole-exome sequencing in the SMZL discovery panel. Table S4 illustrates the segments (regions) of tumor-acquired copy number alterations identified in the SMZL discovery panel. Table S5 and Table S6 list the patient’s features in the screening and extension panel, respectively, Table S7 shows the mutations identified in the screening and extension panels by targeted resequencing of candidate genes. Table S8 reports the copy number aberrations encompassing any of the 61 genes that were subjected to targeted resequencing. Table S9 relates the genetic, immunogenetic and biological features of SMZL and the mutations of MZ development genes. Online supplemental material is available at http://www.jem.org/cgi/content/full/jem.20120904/DC1. Supplementary Material Supplemental Material
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            Regression of splenic lymphoma with villous lymphocytes after treatment of hepatitis C virus infection.

            Some epidemiologic studies suggest a link between hepatitis C virus (HCV) infection and some B-cell non-Hodgkin's lymphomas. We undertook this study after a patient with splenic lymphoma with villous lymphocytes had a hematologic response after antiviral treatment of HCV infection. Nine patients who had splenic lymphoma with villous lymphocytes and HCV infection were treated with interferon alfa-2b (3 million IU three times per week) alone or in combination with ribavirin (1000 to 1200 mg per day). The outcomes were compared with those of six similarly treated patients with splenic lymphoma with villous lymphocytes who tested negative for HCV infection. Of the nine patients with HCV infection who received interferon alfa, seven had a complete remission after the loss of detectable HCV RNA. The other two patients had a partial and a complete remission after the addition of ribavirin and the loss of detectable HCV RNA. One patient had a relapse when the HCV RNA load again became detectable in blood. In contrast, none of the six HCV-negative patients had a response to interferon therapy. In patients with splenic lymphoma with villous lymphocytes who are infected with HCV, treatment with interferon can lead to regression of the lymphoma.
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              Hepatitis C virus induces a mutator phenotype: enhanced mutations of immunoglobulin and protooncogenes.

              Hepatitis C virus (HCV) is a nonretroviral oncogenic RNA virus, which is frequently associated with hepatocellular carcinoma (HCC) and B cell lymphoma. We demonstrated here that acute and chronic HCV infection caused a 5- to 10-fold increase in mutation frequency in Ig heavy chain, BCL-6, p53, and beta-catenin genes of in vitro HCV-infected B cell lines and HCV-associated peripheral blood mononuclear cells, lymphomas, and HCCs. The nucleotide-substitution pattern of p53 and beta-catenin was different from that of Ig heavy chain in HCV-infected cells, suggesting two different mechanisms of mutation. In addition, the mutated protooncogenes were amplified in HCV-associated lymphomas and HCCs, but not in lymphomas of nonviral origin or HBV-associated HCC. HCV induced error-prone DNA polymerase zeta, polymerase iota, and activation-induced cytidine deaminase, which together, contributed to the enhancement of mutation frequency, as demonstrated by the RNA interference experiments. These results indicate that HCV induces a mutator phenotype and may transform cells by a hit-and-run mechanism. This finding provides a mechanism of oncogenesis for an RNA virus.
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                Author and article information

                Journal
                Zhonghua Xue Ye Xue Za Zhi
                Zhonghua Xue Ye Xue Za Zhi
                CJH
                Chinese Journal of Hematology
                Editorial office of Chinese Journal of Hematology (No. 288, Nanjing road, Heping district, Tianjin )
                0253-2727
                2707-9740
                April 2016
                : 37
                : 4
                : 348-352
                Affiliations
                [1]300020 天津,中国医学科学院、北京协和医学院血液学研究所、血液病医院;实验血液学国家重点实验室Institute of Hematology and Blood Diseases Hospital. CAMS & PUMC, Tianjin 300020, China
                Author notes
                通信作者:邱录贵(Qiu Lugui),Email: drqiu99@ 123456medmail.com.cn
                Article
                cjh-37-04-348
                10.3760/cma.j.issn.0253-2727.2016.04.022
                7343092
                27094004
                7a1829f0-b8f3-45cb-9194-887b70fbfc9f
                2016年版权归中华医学会所有Copyright © 2016 by Chinese Medical Association

                This work is licensed under a Creative Commons Attribution 3.0 License (CC-BY-NC). The Copyright own by Publisher. Without authorization, shall not reprint, except this publication article, shall not use this publication format design. Unless otherwise stated, all articles published in this journal do not represent the views of the Chinese Medical Association or the editorial board of this journal.

                History
                : 15 December 2015
                Funding
                基金项目:国家自然科学基金(81200395、81370632);国家科技支撑计划项目(2014BAI09B12);天津市应用基础与前沿技术研究计划(15JCYBJC25100、15JCYBJC27900)
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